Dex: high-performance exploration on large graphs for information retrieval

  • Authors:

  • Norbert Martínez-Bazan;Victor Muntés-Mulero;Sergio Gómez-Villamor;Jordi Nin;Mario-A. Sánchez-Martínez;Josep-L. Larriba-Pey

  • Affiliations:

  • Universitat Politècnica de Catalunya, Barcelona, Spain;Universitat Politècnica de Catalunya, Barcelona, Spain;Universitat Politècnica de Catalunya, Barcelona, Spain;IIIA-CSIC, Bellaterra, Spain;Universitat Politècnica de Catalunya, Barcelona, Spain;Universitat Politècnica de Catalunya, Barcelona, Spain

  • Venue:
  • Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
  • Year:
  • 2007

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Abstract

Link and graph analysis tools are important devices to boost the richness of information retrieval systems. Internet and the existing social networking portals are just a couple of situations where the use of these tools would be beneficial and enriching for the users and the analysts. However, the need for integrating different data sources and, even more important, the need for high performance generic tools, is at odds with the continuously growing size and number of data repositories. In this paper we propose and evaluate DEX, a high performance graph database querying system that allows for the integration of multiple data sources. DEX makes graph querying possible in different flavors, including link analysis, social network analysis, pattern recognition and keyword search. The richness of DEX shows up in the experiments that we carried out on the Internet Movie Database (IMDb). Through a variety of these complex analytical queries, DEX shows to be a generic and efficient tool on large graph databases.